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Interactions between cancer cells and immune cells in the tumor microenvironment influence tumor growth and can contribute to the response to cancer immunotherapies. It is difficult to gain mechanistic insights into the effects of cell–cell interactions in tumors using a purely experimental approach. However, computational modeling enables quantitative investigation of the tumor microenvironment, and agent-based modeling, in particular, provides relevant biological insights into the spatial and temporal evolution of tumors. Here, we develop a novel agent-based model (ABM) to predict the consequences of intercellular interactions. Furthermore, we leverage our prior work that predicts the transitions of CD8+ T cells from a naïve state to a terminally differentiated state using Boolean modeling. Given the details incorporated to predict T cell state, we apply the integrated Boolean–ABM framework to study how the properties of CD8+ T cells influence the composition and spatial organization of tumors and the efficacy of an immune checkpoint blockade. Overall, we present a mechanistic understanding of tumor evolution that can be leveraged to study targeted immunotherapeutic strategies.

Background Fibrotic interstitial lung disease (ILD) is frequently associated with abnormal oxygenation; however, little is known about the accuracy of oxygen saturation by pulse oximetry (SpO2) compared with arterial blood gas (ABG) saturation (SaO2), the factors that influence the partial pressure of carbon dioxide (PaCO2) and the impact of PaCO2 on outcomes in patients with fibrotic ILD.Study design and methods Patients with fibrotic ILD enrolled in a large prospective registry with a room air ABG were included. Prespecified analyses included testing the correlation between SaO2 and SpO2, the difference between SaO2 and SpO2, the association of baseline characteristics with both the difference between SaO2 and SpO2 and the PaCO2, the association of baseline characteristics with acid-base category, and the association of PaCO2 and acid-base category with time to death or transplant.Results A total of 532 patients with fibrotic ILD were included. Mean resting SaO2 was 92±4% and SpO2 was 95±3%. Mean PaCO2 was 38±6 mmHg, with 135 patients having PaCO2 45 mmHg. Correlation between SaO2 and SpO2 was mild to moderate (r=0.39), with SpO2 on average 3.0% higher than SaO2. No baseline characteristics were associated with the difference in SaO2 and SpO2. Variables associated with either elevated or abnormal (elevated or low) PaCO2 included higher smoking pack-years and lower baseline forced vital capacity (FVC). Lower baseline lung function was associated with an increased risk of chronic respiratory acidosis. PaCO2 and acid-base status were not associated with time to death or transplant.Interpretation SaO2 and SpO2 are weakly-to-moderately correlated in fibrotic ILD, with limited ability to accurately predict this difference. Abnormal PaCO2 was associated with baseline FVC but was not associated with outcomes.

Abstract Background Microbial communities play a crucial role in ecosystem function through metabolic interactions. Genome-scale modeling is a promising method to understand these interactions and identify strategies to optimize the community. Flux balance analysis (FBA) is most often used to predict the flux through all reactions in a genome-scale model; however, the fluxes predicted by FBA depend on a user-defined cellular objective. Flux sampling is an alternative to FBA, as it provides the range of fluxes possible within a microbial community. Furthermore, flux sampling can capture additional heterogeneity across a population, especially when cells exhibit sub-maximal growth rates. Results In this study, we simulate the metabolism of microbial communities and compare the metabolic characteristics found with FBA and flux sampling. With sampling, we find significant differences in the predicted metabolism, including an increase in cooperative interactions and pathway-specific changes in predicted flux. Conclusions Our results suggest the importance of sampling-based approaches to evaluate metabolic interactions. Furthermore, we emphasize the utility of flux sampling in quantitatively studying interactions between cells and organisms.

Iochroma orozcoae A.Orejuela & S.D.Sm., sp. nov. (Solanaceae) is described from the Andean forests of Cundinamarca in the eastern cordillera of Colombia. Iochroma orozcoae was first collected by the eminent Spanish priest and botanist José Celestino Mutis in the late part of the 18th century, but the specimens have lain unrecognised in herbaria for over 200 years. The species shares many features with its closest relative, Iochroma baumii S.D.Sm. & S.Leiva, but it differs from it in having small flowers with five corolla lobes and few inflorescences per branch, located near the shoot apex with 1 to 4 (–8) flowers, fruits that are greenish-yellow when ripe and its restricted geographic distribution. A description of I. orozcoae is provided, along with a detailed illustration, photographs of live plants, a comparison with closely-related species and a key to all Colombian species of Iochroma Benth. In closing, we emphasise the value of historical collections for the knowledge of biodiversity.

Abstract T cells play a key role in a variety of immune responses, including infection and cancer. Upon stimulation, naïve CD8+ T cells proliferate and differentiate into a variety of memory and effector cell types; however, failure to clear antigens causes prolonged stimulation of CD8+ T cells, ultimately leading to T cell exhaustion (TCE). The functional and phenotypic changes that occur during CD8+ T cell differentiation are well characterized, but the underlying gene expression state changes are not completely understood. Here, we utilize a previously published data-driven Boolean model of gene regulatory interactions shown to mediate TCE. Our network analysis and modeling reveal the final gene expression states that correspond to TCE, along with the sequence of gene expression patterns that give rise to those final states. With a model that predicts the changes in gene expression that lead to TCE, we could evaluate strategies to inhibit the exhausted state. Overall, we demonstrate that a common pathway model of CD8+ T cell gene regulatory interactions can provide insights into the transcriptional changes underlying the evolution of cell states in TCE.

Abstract Carbapenemase‐resistant Klebsiella pneumoniae (KP) resistant to multiple antibiotic classes necessitates optimized combination therapy. Our objective is to build a workflow leveraging omics and bacterial count data to identify antibiotic mechanisms that can be used to design and optimize combination regimens. For pharmacodynamic (PD) analysis, previously published static time‐kill studies (J Antimicrob Chemother 70, 2015, 2589) were used with polymyxin B (PMB) and chloramphenicol (CHL) mono and combination therapy against three KP clinical isolates over 24 h. A mechanism‐based model (MBM) was developed using time‐kill data in S‐ADAPT describing PMB‐CHL PD activity against each isolate. Previously published results of PMB (1 mg/L continuous infusion) and CHL (Cmax: 8 mg/L; bolus q6h) mono and combination regimens were evaluated using an in vitro one‐compartment dynamic infection model against a KP clinical isolate (108 CFU/ml inoculum) over 24 h to obtain bacterial samples for multi‐omics analyses. The differentially expressed genes and metabolites in these bacterial samples served as input to develop a partial least squares regression (PLSR) in R that links PD responses with the multi‐omics responses via a multi‐omics pathway analysis. PMB efficacy was increased when combined with CHL, and the MBM described the observed PD well for all strains. The PLSR consisted of 29 omics inputs and predicted MBM PD response (R2 = 0.946). Our analysis found that CHL downregulated metabolites and genes pertinent to lipid A, hence limiting the emergence of PMB resistance. Our workflow linked insights from analysis of multi‐omics data with MBM to identify biological mechanisms explaining observed PD activity in combination therapy.

Accurate information about interactions between group I metals and nucleic acids is required to understand the roles these metals play in basic cellular functions, disease progression, and pharmaceuticals, as well as to aid the design of new energy storage materials and nucleic acid sensors that target metal contaminants, among other applications. From this perspective, this work generates a complete CCSD(T)/CBS data set of the binding energies for 64 complexes involving each group I metal (Li+, Na+, K+, Rb+, or Cs+) directly coordinated to various sites in each nucleic acid component (A, C, G, T, U, or dimethylphosphate). This data have otherwise been challenging to determine experimentally, with highly accurate information missing for many group I metal–nucleic acid combinations and no data available for the (charged) phosphate moiety. Subsequently, the performance of 61 DFT methods in combination with def2-TZVPP is tested against the newly generated CCSD(T)/CBS reference values. Detailed analysis of the results reveals that functional performance is dependent on the identity of the metal (with increased errors as group I is descended) and nucleic acid binding site (with larger errors for select purine coordination sites). Over all complexes considered, the best methods include the mPW2-PLYP double-hybrid and ωB97M-V RSH functionals (≤1.6% MPE;

Summary: Colorectal cancer (CRC) shows high incidence and mortality, partly due to the tumor microenvironment (TME), which is viewed as an active promoter of disease progression. Macrophages are among the most abundant cells in the TME. These immune cells are generally categorized as M1, with inflammatory and anti-cancer properties, or M2, which promote tumor proliferation and survival. Although the M1/M2 subclassification scheme is strongly influenced by metabolism, the metabolic divergence between the subtypes remains poorly understood. Therefore, we generated a suite of computational models that characterize the M1- and M2-specific metabolic states. Our models show key differences between the M1 and M2 metabolic networks and capabilities. We leverage the models to identify metabolic perturbations that cause the metabolic state of M2 macrophages to more closely resemble M1 cells. Overall, this work increases understanding of macrophage metabolism in CRC and elucidates strategies to promote the metabolic state of anti-tumor macrophages.

Obligate intracellular pathogens occupy one of two niches – free in the host cell cytoplasm or confined in a membrane-bound vacuole. Pathogens occupying membrane-bound vacuoles are sequestered from the innate immune system and have an extra layer of protection from antimicrobial drugs. However, this lifestyle presents several challenges. First, the bacteria must obtain membrane or membrane components to support vacuole expansion and provide space for the increasing bacteria numbers during the log phase of replication. Second, the vacuole microenvironment must be suitable for the unique metabolic needs of the pathogen. Third, as most obligate intracellular bacterial pathogens have undergone genomic reduction and are not capable of full metabolic independence, the bacteria must have mechanisms to obtain essential nutrients and resources from the host cell. Finally, because they are separated from the host cell by the vacuole membrane, the bacteria must possess mechanisms to manipulate the host cell, typically through a specialized secretion system which crosses the vacuole membrane. While there are common themes, each bacterial pathogen utilizes unique approach to establishing and maintaining their intracellular niches. In this review, we focus on the vacuole-bound intracellular niches of Anaplasma phagocytophilum, Ehrlichia chaffeensis, Chlamydia trachomatis, and Coxiella burnetii.

ABSTRACT Coxiella burnetii is an intracellular bacterium that causes the human disease Q fever. C. burnetii forms a large, acidic Coxiella-containing vacuole (CCV) and uses a type 4B secretion system to secrete effector proteins into the host cell cytoplasm. While the CCV membrane is rich in sterols, cholesterol accumulation in the CCV is bacteriolytic, suggesting that C. burnetii regulation of lipid transport and metabolism is critical for successful infection. The mammalian lipid transport protein ORP1L (oxysterol binding protein-like protein 1 Long) localizes to the CCV membrane and mediates CCV-endoplasmic reticulum (ER) membrane contact sites. ORP1L functions in lipid sensing and transport, including cholesterol efflux from late endosomes and lysosomes (LELs), and the ER. Its sister isoform, ORP1S (oxysterol binding protein-like protein 1 Short) also binds cholesterol but has cytoplasmic and nuclear localization. In ORP1-null cells, we found that CCVs were smaller than in wild-type cells, highlighting the importance of ORP1 in CCV development. This effect was consistent between HeLa cells and murine alveolar macrophages (MH-S cells). CCVs in ORP1-null cells had higher cholesterol content than CCVs in wild-type cells at 4 days of infection, suggesting ORP1 functions in cholesterol efflux from the CCV. While the absence of ORP1 led to a C. burnetii growth defect in MH-S cells, there was no growth defect in HeLa cells. Together, our data demonstrated that C. burnetii uses the host sterol transport protein ORP1 to promote CCV development, potentially by using ORP1 to facilitate cholesterol efflux from the CCV to diminish the bacteriolytic effects of cholesterol. IMPORTANCE Coxiella burnetii is an emerging zoonotic pathogen and bioterrorism threat. No licensed vaccine exists in the United States, and the chronic form of the disease is difficult to treat and potentially lethal. Postinfectious sequelae of C. burnetii infection, including debilitating fatigue, place a significant burden on individuals and communities recovering from an outbreak. C. burnetii must manipulate host cell processes in order to promote infection. Our results establish a link between host cell lipid transport processes and C. burnetii’s avoidance of cholesterol toxicity during infection of alveolar macrophages. Elucidating the mechanisms behind bacterial manipulation of the host will yield insight for new strategies to combat this intracellular pathogen.

Abstract Background Chimeric antigen receptor (CAR)-expressing cells are a powerful modality of adoptive cell therapy against cancer. The potency of signaling events initiated upon antigen binding depends on the costimulatory domain within the structure of the CAR. One such costimulatory domain is 4-1BB, which affects cellular response via the NFκB pathway. However, the quantitative aspects of 4-1BB-induced NFκB signaling are not fully understood. Methods We developed an ordinary differential equation-based mathematical model representing canonical NFκB signaling activated by CD19scFv-4-1BB. After a global sensitivity analysis on model parameters, we ran Monte Carlo simulations of cell population-wide variability in NFκB signaling and quantified the mutual information between the extracellular signal and different levels of the NFκB signal transduction pathway. Results In response to a wide range of antigen concentrations, the magnitude of the transient peak in NFκB nuclear concentration varies significantly, while the timing of this peak is relatively consistent. Global sensitivity analysis showed that the model is robust to variations in parameters, and thus, its quantitative predictions would remain applicable to a broad range of parameter values. The model predicts that overexpressing NEMO and disabling IKKβ deactivation can increase the mutual information between antigen levels and NFκB activation. Conclusions Our modeling predictions provide actionable insights to guide CAR development. Particularly, we propose specific manipulations to the NFκB signal transduction pathway that can fine-tune the response of CD19scFv-4-1BB cells to the antigen concentrations they are likely to encounter. Video Abstract

Agent-based models (ABMs) have enabled great advances in the study of tumor development and therapeutic response, allowing researchers to explore the spatiotemporal evolution of the tumor and its microenvironment. However, these models face serious drawbacks in the realm of parameterization - ABM parameters are typically set individually based on various data and literature sources, rather than through a rigorous parameter estimation approach. While ABMs can be fit to simple time-course data (such as tumor volume), that type of data loses the spatial information that is a defining feature of ABMs. While tumor images provide spatial information, it is exceedingly difficult to compare tumor images to ABM simulations beyond a qualitative visual comparison. Without a quantitative method of comparing the similarity of tumor images to ABM simulations, a rigorous parameter fitting is not possible. Here, we present a novel approach that applies neural networks to represent both tumor images and ABM simulations as low dimensional points, with the distance between points acting as a quantitative measure of difference between the two. This enables a quantitative comparison of tumor images and ABM simulations, where the distance between simulated and experimental images can be minimized using standard parameter-fitting algorithms. Here, we describe this method and present two examples to demonstrate the application of the approach to estimate parameters for two distinct ABMs. Overall, we provide a novel method to robustly estimate ABM parameters.

Pancreatic β-cells respond to increased extracellular glucose levels by initiating a metabolic shift. That change in metabolism is part of the process of glucose-stimulated insulin secretion and is of particular interest in the context of diabetes. However, we do not fully understand how the coordinated changes in metabolic pathways and metabolite products influence insulin secretion. In this work, we apply systems biology approaches to develop a detailed kinetic model of the intracellular central carbon metabolic pathways in pancreatic β-cells upon stimulation with high levels of glucose. The model is calibrated to published metabolomics datasets for the INS1 823/13 cell line, accurately capturing the measured metabolite fold-changes. We first employed the calibrated mechanistic model to estimate the stimulated cell's fluxome. We then used the predicted network fluxes in a data-driven approach to build a partial least squares regression model. By developing the combined kinetic and data-driven modeling framework, we gain insights into the link between β-cell metabolism and glucose-stimulated insulin secretion. The combined modeling framework was used to predict the effects of common anti-diabetic pharmacological interventions on metabolite levels, flux through the metabolic network, and insulin secretion. Our simulations reveal targets that can be modulated to enhance insulin secretion. The model is a promising tool to contextualize and extend the usefulness of metabolomics data and to predict dynamics and metabolite levels that are difficult to measure in vitro. In addition, the modeling framework can be applied to identify, explain, and assess novel and clinically-relevant interventions that may be particularly valuable in diabetes treatment.

Abstract The tomato (Solanum lycopersicum L.) family, Solanaceae, is a model clade for a wide range of applied and basic research questions. Currently, reference‐quality genomes are available for over 30 species from seven genera, and these include numerous crops as well as wild species [e.g., Jaltomata sinuosa (Miers) Mione and Nicotiana attenuata Torr. ex S. Watson]. Here we present the genome of the showy‐flowered Andean shrub Iochroma cyaneum (Lindl.) M. L. Green, a woody lineage from the tomatillo (Physalis philadelphica Lam.) subfamily Physalideae. The assembled size of the genome (2.7 Gb) is more similar in size to pepper (Capsicum annuum L.) (2.6 Gb) than to other sequenced diploid members of the berry clade of Solanaceae [e.g., potato (Solanum tuberosum L.), tomato, and Jaltomata]. Our assembly recovers 92% of the conserved orthologous set, suggesting a nearly complete genome for this species. Most of the genomic content is repetitive (69%), with Gypsy elements alone accounting for 52% of the genome. Despite the large amount of repetitive content, most of the 12 I. cyaneum chromosomes are highly syntenic with tomato. Bayesian concordance analysis provides strong support for the berry clade, including I. cyaneum, but reveals extensive discordance along the backbone, with placement of chili pepper and Jaltomata being highly variable across gene trees. The I. cyaneum genome contributes to a growing wealth of genomic resources in Solanaceae and underscores the need for expanded sampling of diverse berry genomes to dissect major morphological transitions.

Context Sleep is critical for optimal childhood metabolic health and neurodevelopment. However, there is limited knowledge regarding childhood sex differences in sleep, including children with neurodevelopmental disorders, and the impact of such differences on metabolic health. Objective To evaluate if sex differences in childhood sleep exist and if sleep associates with metabolic health outcomes equally by sex. Using autism spectrum disorder (ASD) as a case study, we also examine sleep sex differences in children with a neurodevelopmental disorder. Methods A narrative review explored the literature focussing on sex differences in childhood sleep. Results Sex differences in sleep were not detected among pre-adolescents. However, female adolescents were more likely to report impaired sleep than males. Childhood obesity is more common in males. Shorter sleep duration may be associated with obesity in male pre-adolescents/adolescents; although findings are mixed. ASD is male-predominant; yet, there was an indication that pre-adolescent female children with ASD had more impaired sleep. Conclusion Sex differences in sleep appear to emerge in adolescence with more impaired sleep in females. This trend was also observed among pre-adolescent female children with ASD. Further research is needed on sex differences in childhood sleep and metabolic health and the underlying mechanisms driving these differences.

In recent decades, chimeric antigen receptors (CARs) have been successfully used to generate engineered T cells capable of recognizing and eliminating cancer cells. The structure of CARs typically includes costimulatory domains, which enhance the T-cell response upon antigen encounter. However, it is not fully known how those co-stimulatory domains influence cell activation in the presence of biological variability. In this work, we used mathematical modelling to elucidate how the inclusion of one such costimulatory molecule, CD28, impacts the response of a population of CAR T cells under different sources of variability. Particularly, we demonstrate that CD28-bearing CARs mediate a faster and more consistent population response under both target antigen variability and kinetic rate variability. Next, we identify kinetic parameters that have the most impact on cell response time. Finally, based on our findings, we propose that enhancing the catalytic activity of lymphocyte-specific protein tyrosine kinase can result in drastically reduced and more consistent response times among heterogeneous CAR T-cell populations.

Abstract Evolutionary genetic studies have uncovered abundant evidence for genomic hotspots of phenotypic evolution, as well as biased patterns of mutations at those loci. However, the theoretical basis for this concentration of particular types of mutations at particular loci remains largely unexplored. In addition, historical contingency is known to play a major role in evolutionary trajectories, but has not been reconciled with the existence of such hotspots. For example, do the appearance of hotspots and the fixation of different types of mutations at those loci depend on the starting state and/or on the nature and direction of selection? Here, we use a computational approach to examine these questions, focusing the anthocyanin pigmentation pathway, which has been extensively studied in the context of flower color transitions. We investigate two transitions that are common in nature, the transition from blue to purple pigmentation and from purple to red pigmentation. Both sets of simulated transitions occur with a small number of mutations at just four loci and show strikingly similar peaked shapes of evolutionary trajectories, with the mutations of the largest effect occurring early but not first. Nevertheless, the types of mutations (biochemical vs. regulatory) as well as their direction and magnitude are contingent on the particular transition. These simulated color transitions largely mirror findings from natural flower color transitions, which are known to occur via repeated changes at a few hotspot loci. Still, some types of mutations observed in our simulated color evolution are rarely observed in nature, suggesting that pleiotropic effects further limit the trajectories between color phenotypes. Overall, our results indicate that the branching structure of the pathway leads to a predictable concentration of evolutionary change at the hotspot loci, but the types of mutations at these loci and their order is contingent on the evolutionary context.

Abstract In order to promote continued growth, a tumor must recruit new blood vessels, a process known as tumor angiogenesis. Many therapies have been tested that aim to inhibit tumor angiogenesis, with the goal of starving the tumor of nutrients and preventing tumor growth. However, many of these therapies have been unsuccessful and can paradoxically further tumor development by leading to increased local tumor invasion and metastasis. In this study, we use agent‐based modeling to examine how hypoxic and acidic conditions following anti‐angiogenic therapy can influence tumor development. Under these conditions, we find that cancer cells experience a phenotypic shift to a state of higher survival and invasive capability, spreading further away from the tumor into the surrounding tissue. Although anti‐angiogenic therapy alone promotes tumor cell adaptation and invasiveness, we find that augmenting chemotherapy with anti‐angiogenic therapy improves chemotherapeutic response and delays the time it takes for the tumor to regrow. Overall, we use computational modeling to explain the behavior of tumor cells in response to anti‐angiogenic treatment in the dynamic tumor microenvironment.

Abstract Background Angiogenesis plays an important role in the survival of tissues, as blood vessels provide oxygen and nutrients required by the resident cells. Thus, targeting angiogenesis is a prominent strategy in many different settings, including both tissue engineering and cancer treatment. However, not all of the approaches that modulate angiogenesis lead to successful outcomes. Angiogenesis-based therapies primarily target pro-angiogenic factors such as vascular endothelial growth factor-A (VEGF) or fibroblast growth factor (FGF) in isolation, and there is a limited understanding of how these promoters combine together to stimulate angiogenesis. Targeting one pathway could be insufficient, as alternative pathways may compensate, diminishing the overall effect of the treatment strategy. Methods To gain mechanistic insight and identify novel therapeutic strategies, we have developed a detailed mathematical model to quantitatively characterize the crosstalk of FGF and VEGF intracellular signaling. The model focuses on FGF- and VEGF-induced mitogen-activated protein kinase (MAPK) signaling to promote cell proliferation and the phosphatidylinositol 3-kinase/protein kinase B (PI3K/Akt) pathway, which promotes cell survival and migration. We fit the model to published experimental datasets that measure phosphorylated extracellular regulated kinase (pERK) and Akt (pAkt) upon FGF or VEGF stimulation. We validate the model with separate sets of data. Results We apply the trained and validated mathematical model to characterize the dynamics of pERK and pAkt in response to the mono- and co-stimulation by FGF and VEGF. The model predicts that for certain ranges of ligand concentrations, the maximum pERK level is more responsive to changes in ligand concentration compared to the maximum pAkt level. Also, the combination of FGF and VEGF indicates a greater effect in increasing the maximum pERK compared to the summation of individual effects, which is not seen for maximum pAkt levels. In addition, our model identifies the influential species and kinetic parameters that specifically modulate the pERK and pAkt responses, which represent potential targets for angiogenesis-based therapies. Conclusions Overall, the model predicts the combination effects of FGF and VEGF stimulation on ERK and Akt quantitatively and provides a framework to mechanistically explain experimental results and guide experimental design. Thus, this model can be utilized to study the effects of pro- and anti-angiogenic therapies that particularly target ERK and/or Akt activation upon stimulation with FGF and VEGF. Video Abstract

ABSTRACT Coxiella burnetii replicates in a phagolysosome-like vacuole called the Coxiella-containing vacuole (CCV). While host cholesterol readily traffics to the CCV, cholesterol accumulation leads to CCV acidification and bacterial death. Thus, bacterial regulation of CCV cholesterol content is essential for Coxiella pathogenesis. Coxiella expresses a sterol-modifying protein, Stmp1, that may function to lower CCV cholesterol through enzymatic modification. Using an Stmp1 knockout (Δstmp1), we determined that Stmp1 is not essential for axenic growth. Inside host cells, however, Δstmp1 mutant bacteria form smaller CCVs which accumulate cholesterol, preferentially fuse with lysosomes, and become more acidic, correlating with a significant growth defect. However, in cholesterol-free cells, Δstmp1 mutant bacteria grow similarly to wild-type bacteria but are hypersensitive to cholesterol supplementation. To better understand the underlying mechanism behind the Δstmp1 mutant phenotype, we performed sterol profiling. Surprisingly, we found that Δstmp1 mutant-infected macrophages accumulated the potent cholesterol homeostasis regulator 25-hydroxycholesterol (25-HC). We next determined whether dysregulated 25-HC alters Coxiella infection by treating wild-type Coxiella-infected cells with 25-HC. Similar to the Δstmp1 mutant phenotype, 25-HC increased CCV proteolytic activity and inhibited bacterial growth. Collectively, these data indicate that Stmp1 alters host cholesterol metabolism and is essential to establish a mature CCV which supports Coxiella growth. IMPORTANCE Coxiella burnetii is the causative agent of human Q fever, an emerging infectious disease and significant cause of culture-negative endocarditis. Acute infections are often undiagnosed, there are no licensed vaccines in the United States, and chronic Q fever requires a prolonged antibiotic treatment. Therefore, new treatment and preventive options are critically needed. Coxiella is an obligate intracellular bacterium that replicates within a large acidic phagolysosome-like compartment, the Coxiella-containing vacuole (CCV). We previously discovered that cholesterol accumulation in the CCV increases its acidification, leading to bacterial death. Therefore, in order to survive in this harsh environment, Coxiella likely regulates CCV cholesterol levels. Here, we found that Coxiella sterol modifying protein (Stmp1) facilitates bacterial growth by reducing CCV cholesterol and host cell 25-hydroxycholesterol (25-HC) levels, which prevents excessive CCV fusion with host lysosomes and CCV acidification. This study establishes that Stmp1-mediated regulation of host cholesterol homeostasis is essential for Coxiella intracellular survival.

Evolving in sync with the computation revolution over the past 30 years, computational biology has emerged as a mature scientific field. While the field has made major contributions toward improving scientific knowledge and human health, individual computational biology practitioners at various institutions often languish in career development. As optimistic biologists passionate about the future of our field, we propose solutions for both eager and reluctant individual scientists, institutions, publishers, funding agencies, and educators to fully embrace computational biology. We believe that in order to pave the way for the next generation of discoveries, we need to improve recognition for computational biologists and better align pathways of career success with pathways of scientific progress. With 10 outlined steps, we call on all adjacent fields to move away from the traditional individual, single-discipline investigator research model and embrace multidisciplinary, data-driven, team science.

Percutaneous closure of a patent foramen ovale (PFO) reduces the risk of recurrent cryptogenic stroke specifically in younger patients. The three randomized controlled trials that led to the widespread adoption of PFO closure excluded patients over the age of 60 years. Older patients frequently have other cardiac and vascular conditions that are common risk factors for stroke, whereas paradoxical embolism through a PFO is relatively rare. Younger patients theoretically benefit the most from closure due to longer lifetime exposure risk and absence of other traditional risk factors. PFO in older patients with cryptogenic strokes is often encountered in clinical practice, making up an increasing number of cardiology referrals, yet cardiologists lack guidelines and evaluation tools for these patients. This review explores the history of PFO closure – emphasizing data in older adults – and discusses the evaluation and treatment of older people with cryptogenic stroke and PFO while further trials in this important population are awaited.

Translational control (TC) is one the crucial steps that dictate gene expression and alter the outcome of physiological process like programmed cell death, metabolism, and proliferation in a eukaryotic cell. TC occurs mainly at the translation initiation stage. The initiation factor eIF5B tightly regulates global translation initiation and facilitates the expression of a subset of proteins involved in proliferation, inhibition of apoptosis, and immunosuppression under stress conditions. eIF5B enhances the expression of these survival proteins to allow cancer cells to metastasize and resist chemotherapy. Using eIF5B as a biomarker or drug target could help with diagnosis and improved prognosis, respectively. To achieve these goals, it is crucial to understand the role of eIF5B in translational regulation. This review recapitulates eIF5B’s regulatory roles in the translation initiation of viral mRNA as well as the cellular mRNAs in cancer and stressed eukaryotic cells.

Abstract Vascular endothelial growth factor (VEGF) is a strong promoter of angiogenesis in tumors, and anti‐VEGF treatment, such as a humanized antibody to VEGF, is clinically used as a monotherapy or in combination with chemotherapy to treat cancer patients. However, this approach is not effective in all patients or cancer types. To better understand the heterogeneous responses to anti‐VEGF and the synergy between anti‐VEGF and other anticancer therapies, we constructed a computational model characterizing angiogenesis‐mediated growth of in vivo mouse tumor xenografts. The model captures VEGF‐mediated cross‐talk between tumor cells and endothelial cells and is able to predict the details of molecular‐ and cellular‐level dynamics. The model predictions of tumor growth in response to anti‐VEGF closely match the quantitative measurements from multiple preclinical mouse studies. We applied the model to investigate the effects of VEGF‐targeted treatment on tumor cells and endothelial cells. We identified that tumors with lower tumor cell growth rate and higher carrying capacity have a stronger response to anti‐VEGF treatment. The predictions indicate that the variation of tumor cell growth rate can be a main reason for the experimentally observed heterogeneous response to anti‐VEGF. In addition, our simulation results suggest a new synergy mechanism where anticancer therapy can enhance anti‐VEGF simply through reducing the tumor cell growth rate. Overall, this work generates novel insights into the heterogeneous response to anti‐VEGF treatment and the synergy of anti‐VEGF with other therapies, providing a tool that be further used to test and optimize anticancer therapy.

(1) Background: ADHD is recognized as one of the most common neurodevelopmental disorders. The worldwide prevalence of ADHD is estimated at 5.3%; however, estimates vary as a function of a number of factors, including diagnostic methods, age, sex and geographical location. A review of studies is needed to clarify the epidemiology of ADHD in Canada. (2) Methods: A search strategy was created in PubMed and adapted for MEDLINE and PsycINFO. Papers were included if they examined diagnosed ADHD prevalence and/or incidence rates in any region of Canada, age group and gender. A snowball technique was used to identify additional papers from reference lists, and experts in the field were consulted. (3) Results: Ten papers included in this review reported on prevalence, and one reported on incidence. One study provided an overall prevalence estimate across provinces for adults of 2.9%, and one study provided an overall estimate across five provinces for children and youth of 8.6%. Across age groups (1 to 24 years), incidence estimates ranged from 0.4% to 1.2%, depending on province. Estimates varied by age, gender, province, region and time. (4) Conclusions: The overall Canadian ADHD prevalence estimate is similar to worldwide estimates for adults. Most studies reported on prevalence rather than incidence. Differences in estimates across provinces may reflect the varying number of practitioners available to diagnose and prescribe medication for ADHD across provinces. To achieve a more comprehensive understanding of the epidemiology of ADHD in Canada, a study is needed that includes all provinces and territories, and that considers estimates in relation to age, gender, ethnicity, geographical region, socioeconomic status and access to mental healthcare coverage. Incidence rates need further examination to be determined.

Natural killer (NK) cells are immune effector cells that can detect and lyse cancer cells. However, NK cell exhaustion, a phenotype characterized by reduced secretion of cytolytic models upon serial stimulation, limits the NK cell's ability to lyse cells. In this work, we investigated in silico strategies that counteract the NK cell's reduced secretion of cytolytic molecules. To accomplish this goal, we constructed a mathematical model that describes the dynamics of the cytolytic molecules granzyme B (GZMB) and perforin-1 (PRF1) and calibrated the model predictions to published experimental data using a Bayesian parameter estimation approach. We applied an information-theoretic approach to perform a global sensitivity analysis, from which we found that the suppression of phosphatase activity maximizes the secretion of GZMB and PRF1. However, simply reducing the phosphatase activity is shown to deplete the cell's intracellular pools of GZMB and PRF1. Thus, we added a synthetic Notch (synNotch) signaling circuit to our baseline model as a method for controlling the secretion of GZMB and PRF1 by inhibiting phosphatase activity and increasing production of GZMB and PRF1. We found that the optimal synNotch system depends on the frequency of NK cell stimulation. For only a few rounds of stimulation, the model predicts that inhibition of phosphatase activity leads to more secreted GZMB and PRF1; however, for many rounds of stimulation, the model reveals that increasing production of the cytolytic molecules is the optimal strategy. In total, we developed a mathematical framework that provides actionable insight into engineering robust NK cells for clinical applications.

Within the tumor microenvironment, macrophages exist in an immunosuppressive state, preventing T cells from eliminating the tumor. Due to this, research is focusing on immunotherapies that specifically target macrophages in order to reduce their immunosuppressive capabilities and promote T cell function. In this study, we develop an agent-based model consisting of the interactions between macrophages, T cells, and tumor cells to determine how the immune response changes due to three macrophage-based immunotherapeutic strategies: macrophage depletion, recruitment inhibition, and macrophage reeducation. We find that reeducation, which converts the macrophages into an immune-promoting phenotype, is the most effective strategy and that the macrophage recruitment rate and tumor proliferation rate (tumor-specific properties) have large impacts on therapy efficacy. We also employ a novel method of using a neural network to reduce the computational complexity of an intracellular signaling mechanistic model.

Vector-borne illnesses comprise a significant portion of human maladies, representing 17% of global infections. Transmission of vector-borne pathogens to mammals primarily occurs by hematophagous arthropods. It is speculated that blood may provide a unique environment that aids in the replication and pathogenesis of these microbes. Lipids and their derivatives are one component enriched in blood and are essential for microbial survival. For instance, the malarial parasite Plasmodium falciparum and the Lyme disease spirochete Borrelia burgdorferi, among others, have been shown to scavenge and manipulate host lipids for structural support, metabolism, replication, immune evasion, and disease severity. In this Review, we will explore the importance of lipid hijacking for the growth and persistence of these microbes in both mammalian hosts and arthropod vectors.

Abstract Long‐term ecological monitoring provides valuable and objective scientific information to inform management and decision‐making. In this article, we analyze 22 years of herpetofauna monitoring data from the Point Loma Ecological Conservation Area (PLECA), an insular urban reserve near San Diego, CA. Our analysis showed that counts of individuals for one of the four most common terrestrial vertebrates declined, whereas counts for other common species increased or remained stable. Two species exhibited declines in adult body length, whereas biomass pooled over the five most common species increased over time and was associated with higher wet season precipitation. Although the habitat and vegetation at PLECA have remained protected and intact, we suspect that changes in arthropod communities may be driving changes in the abundance, growth, and development of insectivorous lizards. This study underscores the value of long‐term monitoring for establishing quantitative baselines to assess biological changes that would otherwise go undetected.

Summary: Chimeric antigen receptors (CARs) are engineered receptors that mediate T cell activation. CARs are comprised of activating and co-stimulatory intracellular signaling domains derived from endogenous T cells that initiate signaling required for T cell activation, including ERK activation through the MAPK pathway. Understanding the mechanisms by which co-stimulatory domains influence signaling can help guide the design of next-generation CARs. Therefore, we constructed an experimentally validated computational model of anti-CD19 CARs in T cells bearing the CD3ζ domain alone or in combination with CD28. We performed a systematic analysis to explore the different mechanisms of CD28 co-stimulation on the ERK response time. Comparing these model simulations with experimental data indicates that CD28 primarily influences ERK activation by enhancing the phosphorylation kinetics of CD3ζ. Overall, we present a mechanistic mathematical modeling framework that can be used to gain insights into the mechanism of CAR T cell activation and produce new testable hypotheses. : Immunology; Immunology Theories; Computational Bioinformatics Subject Areas: Immunology, Immunology Theories, Computational Bioinformatics

As patients recently diagnosed with T1D and patients with T2D have residual beta cell mass, there is considerable effort in beta cell biology to understand the mechanisms that drive beta cell regeneration as a potential cellular therapy for expanding patients’ residual beta cell population. Both mouse and human studies have established that beta cell mass expansion occurs rapidly during pregnancy. To investigate the mechanisms of beta cell mass expansion during pregnancy, we developed a novel in vivo and in vitro models of pseudopregnancy. Our models demonstrate that pseudopregnancy promotes beta cell mass expansion in parous mice, and this expansion is driven by beta cell proliferation rather than hypertrophy. Importantly, estrogen, progesterone, and placental lactogen induce STAT5A signaling in the pseudopregnancy model, demonstrating that this model successfully recapitulates pregnancy-induced beta cell replication. We then created an in vitro model of pseudopregnancy and found that the combination of estrogen and placental lactogen induced beta cell replication in human islets and rat insulinoma cells. Therefore, beta cells both in vitro and in vivo increase proliferation when subjected to the pseudopregnancy cocktail compared to groups treated with estradiol or placental lactogen alone. The pseudopregnancy models described here may help inform novel methods of inducing beta cell replication in patients with diabetes.

Sandra L Carroll,1–3 Gayathri Embuldeniya,3 Jasprit Pannag,1 Krystina B Lewis,4 Jeff S Healey,2,3,5 Michael McGillion,1,2 Lehana Thabane,2,6,7 Dawn Stacey4,8 1School of Nursing, McMaster University, Hamilton, ON, Canada; 2Population Health Research Institute, Hamilton Health Sciences, Hamilton, ON, Canada; 3Hamilton Health Sciences, Hamilton, ON, Canada; 4School of Nursing, University of Ottawa, Ottawa, ON, Canada; 5Department of Medicine, McMaster University, Hamilton, ON, Canada; 6Department of Health Research Methods, Evidence and Impact, McMaster University, Hamilton, ON, Canada; 7Biostatistics Unit, St. Joseph’s Healthcare, Hamilton, ON, Canada; 8Ottawa Hospital Research Institute, Ottawa, ON, Canada Purpose: Patients’ values are a key component of patient-centered care and shared decision making in health care organizations. There is limited understanding on how patients’ values guide their health related decision making or how patients understand the concept of values during these processes. This study investigated patients’ understanding of their values in the context of considering the risks/benefits of receiving an implantable cardioverter-defibrillator (ICD). Patients and methods: A qualitative substudy was conducted within a feasibility trial with first-time ICD candidates randomized to receive a patient decision aid or usual care prior to specialist consultation. Semi-structured interviews were conducted with participants post-implantation or post-specialist consultation. Results: Sixteen patients (ten male) aged 47–87 years participated. Of these, ten (62.5%) received the patient decision aid prior to specialist consultation. Findings revealed patients were confused by the word “values” and had difficulty expressing values related to risks/benefits during ICD decision making. When probed, values were conceptualized broadly capturing other factors such as desire to live, good quality of life, family’s views, ICD information, control over decision, and medical authority. Conclusion: This study revealed the difficulty patients considering an ICD had with articulating their values in the context of an ICD health decision and highlighted the challenge to effectively elicit patients’ values within health decisions overall. It is suggested that there should be a shift away from the use of the word “values” when speaking directly to patients toward language such as “what matters to you the most” or “what is most important to you”. Keywords: values, patient preferences, patient engagement, qualitative, health decision

Upon host cell infection, the obligate intracellular bacterium Coxiella burnetii resides and multiplies within the Coxiella-Containing Vacuole (CCV). The nascent CCV progresses through the endosomal maturation pathway into a phagolysosome, acquiring endosomal and lysosomal markers, as well as acidic pH and active proteases and hydrolases. Approximately 24-48 hours post infection, heterotypic fusion between the CCV and host endosomes/lysosomes leads to CCV expansion and bacterial replication in the mature CCV. Initial CCV acidification is required to activate C. burnetii metabolism and the Type 4B Secretion System (T4BSS), which secretes effector proteins required for CCV maturation. However, we found that the mature CCV is less acidic (pH~5.2) than lysosomes (pH~4.8). Further, inducing CCV acidification to pH~4.8 causes C. burnetii lysis, suggesting C. burnetii actively regulates pH of the mature CCV. Because heterotypic fusion with host endosomes/lysosomes may influence CCV pH, we investigated endosomal maturation in cells infected with wildtype (WT) or T4BSS mutant (ΔdotA) C. burnetii. In WT-infected cells, we observed a significant decrease in proteolytically active, LAMP1-positive endolysosomal vesicles, compared to mock or ΔdotA-infected cells. Using a ratiometric assay to measure endosomal pH, we determined that the average pH of terminal endosomes in WT-infected cells was pH~5.8, compared to pH~4.75 in mock and ΔdotA-infected cells. While endosomes progressively acidified from the periphery (pH~5.5) to the perinuclear area (pH~4.7) in both mock and ΔdotA-infected cells, endosomes did not acidify beyond pH~5.2 in WT-infected cells. Finally, increasing lysosomal biogenesis by overexpressing the transcription factor EB resulted in smaller, more proteolytically active CCVs and a significant decrease in C. burnetii growth, indicating host lysosomes are detrimental to C. burnetii. Overall, our data suggest that C. burnetii inhibits endosomal maturation to reduce the number of proteolytically active lysosomes available for heterotypic fusion with the CCV, possibly as a mechanism to regulate CCV pH.

Abstract Background Thrombospondin-1 (TSP1) is a matricellular protein that functions to inhibit angiogenesis. An important pathway that contributes to this inhibitory effect is triggered by TSP1 binding to the CD36 receptor, inducing endothelial cell apoptosis. However, therapies that mimic this function have not demonstrated clear clinical efficacy. This study explores strategies to enhance TSP1-induced apoptosis in endothelial cells. In particular, we focus on establishing a computational model to describe the signaling pathway, and using this model to investigate the effects of several approaches to perturb the TSP1-CD36 signaling network. Methods We constructed a molecularly-detailed mathematical model of TSP1-mediated intracellular signaling via the CD36 receptor based on literature evidence. We employed systems biology tools to train and validate the model and further expanded the model by accounting for the heterogeneity within the cell population. The initial concentrations of signaling species or kinetic rates were altered to simulate the effects of perturbations to the signaling network. Results Model simulations predict the population-based response to strategies to enhance TSP1-mediated apoptosis, such as downregulating the apoptosis inhibitor XIAP and inhibiting phosphatase activity. The model also postulates a new mechanism of low dosage doxorubicin treatment in combination with TSP1 stimulation. Using computational analysis, we predict which cells will undergo apoptosis, based on the initial intracellular concentrations of particular signaling species. Conclusions This new mathematical model recapitulates the intracellular dynamics of the TSP1-induced apoptosis signaling pathway. Overall, the modeling framework predicts molecular strategies that increase TSP1-mediated apoptosis, which is useful in many disease settings.

Saracha andina Rob. Fernandez, I. Revilla & E. Pariente, sp. nov. (Solanaceae), a new species endemic to the central Andes of Peru, is described here. The new species differs from other species of Saracha Ruiz & Pav. by the combination of small and coriaceous leaves and clearly tubular flowers. A summary of the taxonomic history of the genus Saracha, an identification key for its species and a phylogenetic analysis of this genus and related genera are provided.

Background Sex‐specific criteria are recommended for the diagnosis of myocardial infarction, but the impact of these on presenting characteristics is unknown. Methods and Results We evaluated patient‐reported symptoms in 1941 patients (39% women) with suspected acute coronary syndrome attending the emergency department in a substudy of a prospective trial. Standardized criteria defined typical and atypical presentations based on pain nature, location, radiation, and additional symptoms. Diagnosis of myocardial infarction was adjudicated using a high‐sensitivity cardiac troponin I assay with sex‐specific thresholds (>16 ng/L women, >34 ng/L men). Patients identified who were missed by the contemporary assay with a uniform threshold (≥50 ng/L) were reclassified by this approach. Type 1 myocardial infarction was diagnosed in 16% (184/1185) of men and 12% (90/756) of women, with 9 (5%) men and 27 (30%) women reclassified using high‐sensitivity cardiac troponin I and sex‐specific thresholds. Chest pain was the presenting symptom in 91% (1081/1185) of men and 92% (698/756) of women. Typical symptoms were more common in women than in men with myocardial infarction (77% [69/90] versus 59% [109/184]; P=0.007), and differences were similar in those reclassified (74% [20/27] versus 44% [4/9]; P=0.22). The presence of ≥3 typical features was associated with a positive likelihood ratio for the diagnosis of myocardial infarction in women (positive likelihood ratio, 1.18; 95% CI, 1.03–1.31) but not in men (positive likelihood ratio 1.09; 95% CI, 0.96–1.24). Conclusions Typical symptoms are more common and have greater predictive value in women than in men with myocardial infarction whether or not they are diagnosed using sex‐specific criteria. Clinical Trial Registration URL: http://www.clinicaltrials.gov. Unique identifier NCT01852123.

Tumor angiogenesis is regulated by pro- and anti-angiogenic factors. Anti-angiogenic agents target the interconnected network of angiogenic factors to inhibit neovascularization, which subsequently impedes tumor growth. Due to the complexity of this network, optimizing anti-angiogenic cancer treatments requires detailed knowledge at a systems level. In this study, we constructed a tumor tissue-based model to better understand how the angiogenic network is regulated by opposing mediators at the extracellular level. We consider the network comprised of two pro-angiogenic factors: vascular endothelial growth factor (VEGF) and basic fibroblast growth factor (FGF2), and two anti-angiogenic factors: thrombospondin-1 (TSP1) and platelet factor 4 (PF4). The model’s prediction of angiogenic factors’ distribution in tumor tissue reveals the localization of different factors and indicates the angiogenic state of the tumor. We explored how the distributions are affected by the secretion of the pro- and anti-angiogenic factors, illustrating how the angiogenic network is regulated in the extracellular space. Interestingly, we identified a counterintuitive result that the secretion of the anti-angiogenic factor PF4 can enhance pro-angiogenic signaling by elevating the levels of the interstitial and surface-level pro-angiogenic species. This counterintuitive situation is pertinent to the clinical setting, such as the release of anti-angiogenic factors in platelet activation or the administration of exogenous PF4 for anti-angiogenic therapy. Our study provides mechanistic insights into this counterintuitive result and highlights the role of heparan sulfate proteoglycans in regulating the interactions between angiogenic factors. This work complements previous studies aimed at understanding the formation of angiogenic complexes in tumor tissue and helps in the development of anti-cancer strategies targeting angiogenesis.

Mathematical modeling provides the predictive ability to understand the metabolic reprogramming and complex pathways that mediate cancer cells' proliferation. We present a mathematical model using a multiscale, multicellular approach to simulate avascular tumor growth, applied to pancreatic cancer. The model spans three distinct spatial and temporal scales. At the extracellular level, reaction diffusion equations describe nutrient concentrations over a span of seconds. At the cellular level, a lattice-based energy driven stochastic approach describes cellular phenomena including adhesion, proliferation, viability and cell state transitions, occurring on the timescale of hours. At the sub-cellular level, we incorporate a detailed kinetic model of intracellular metabolite dynamics on the timescale of minutes, which enables the cells to uptake and excrete metabolites and use the metabolites to generate energy and building blocks for cell growth. This is a particularly novel aspect of the model. Certain defined criteria for the concentrations of intracellular metabolites lead to cancer cell growth, proliferation or death. Overall, we model the evolution of the tumor in both time and space. Starting with a cluster of tumor cells, the model produces an avascular tumor that quantitatively and qualitatively mimics experimental measurements of multicellular tumor spheroids. Through our model simulations, we can investigate the response of individual intracellular species under a metabolic perturbation and investigate how that response contributes to the response of the tumor as a whole. The predicted response of intracellular metabolites under various targeted strategies are difficult to resolve with experimental techniques. Thus, the model can give novel predictions as to the response of the tumor as a whole, identifies potential therapies to impede tumor growth, and predicts the effects of those therapeutic strategies. In particular, the model provides quantitative insight into the dynamic reprogramming of tumor cells at the intracellular level in response to specific metabolic perturbations. Overall, the model is a useful framework to study targeted metabolic strategies for inhibiting tumor growth.

Despite being considered one of the most successful neural prostheses, cochlear implants (CIs) provide recipients with a wide range of speech perception performance. While some CI users can understand speech in the absence of visual cues, other recipients exhibit more limited speech perception. Cognitive skills have been documented as a contributor to complex auditory processing, such as language understanding; however, there are no normative data for existing standardized clinical tests assessing cognitive abilities in CI users. Here, we assess the impact of modality of presentation (i.e., auditory-visual versus visual) for the administration of working memory tests in high-performing CI users in addition to measuring processing speed, cognitive efficiency and intelligence quotient (IQ). Second, we relate performance on these cognitive measures to clinical CI speech perception outcomes.Methods: Twenty one post-lingually deafened, high-performing, adult CI users [age range: 52–88 years; 3 unilateral CI, 13 bimodal (i.e., CI with contralateral hearing aid), 5 bilateral CI] with clinical speech perception scores (i.e., AzBio sentences in quiet for the first-ear CI) of ≥60% were recruited. A cognitive test battery assessing auditory-visual working memory (AVWM), visual working memory (VWM), processing speed, cognitive efficiency and IQ was administered, in addition to clinical measures of speech perception in quiet (i.e., AzBio sentences in quiet). AzBio sentences were assessed in two conditions: first-ear CI only, and best-aided everyday wearing condition. Subjects also provided self-reported measures of performance and benefit from their CI using standardized materials, including the Glasgow Benefit Inventory (GBI) and the Nijmegen Cochlear Implant questionnaire (NCIQ).Results: High-performing CI users demonstrated greater VWM than AVWM recall. VWM was positively related to AzBio scores when measured in the first-ear CI only. AVWM, processing speed, cognitive efficiency, and IQ did not relate to either measure of speech perception (i.e., first-ear CI or best-aided conditions). Subjects’ self-reported benefit as measured by the GBI predicted best-aided CI speech perception performance.Conclusion: In high-performing CI recipients, visual presentation of working memory tests may improve our assessment of cognitive function.

Myotonic dystrophy type 1 (DM1) is an inherited disease characterized by the inability to relax contracted muscles. Affected individuals carry large CTG expansions that are toxic when transcribed. One possible treatment approach is to reduce or eliminate transcription of CTG repeats. Actinomycin D (ActD) is a potent transcription inhibitor and FDA-approved chemotherapeutic that binds GC-rich DNA with high affinity. Here, we report that ActD decreased CUG transcript levels in a dose-dependent manner in DM1 cell and mouse models at significantly lower concentrations (nanomolar) compared to its use as a general transcription inhibitor or chemotherapeutic. ActD also significantly reversed DM1-associated splicing defects in a DM1 mouse model, and did so within the currently approved human treatment range. RNA-seq analyses showed that low concentrations of ActD did not globally inhibit transcription in a DM1 mouse model. These results indicate that transcription inhibition of CTG expansions is a promising treatment approach for DM1.

Coxiella burnetii is an obligate intracellular bacterial pathogen and a causative agent of culture-negative endocarditis. While C. burnetii initially infects alveolar macrophages, it has also been found in lipid droplet (LD)-containing foamy macrophages in the cardiac valves of endocarditis patients. In addition, transcriptional studies of C. burnetii-infected macrophages reported differential regulation of the LD coat protein-encoding gene perilipin 2 (plin-2). To further investigate the relationship between LDs and C. burnetii, we compared LD numbers using fluorescence microscopy in mock-infected and C. burnetii-infected alveolar macrophages. On average, C. burnetii-infected macrophages contained twice as many LDs as mock-infected macrophages. LD numbers increased as early as 24 hours post-infection, an effect reversed by blocking C. burnetii protein synthesis. The observed LD accumulation was dependent on the C. burnetii Type 4B Secretion System (T4BSS), a major virulence factor that manipulates host cellular processes by secreting bacterial effector proteins into the host cell cytoplasm. To determine the importance of LDs during C. burnetii infection, we manipulated LD homeostasis and assessed C. burnetii intracellular growth. Surprisingly, blocking LD formation with the pharmacological inhibitors triacsin C or T863, or knocking out acyl-CoA transferase-1 (acat-1) in alveolar macrophages, increased C. burnetii growth at least 2-fold. Conversely, preventing LD lipolysis by inhibiting adipose triglyceride lipase (ATGL) with atglistatin almost completely blocked bacterial growth, suggesting LD breakdown is essential for C. burnetii. Together these data suggest that maintenance of LD homeostasis, possibly via the C. burnetii T4BSS, is critical for bacterial growth.

Tumors exploit angiogenesis, the formation of new blood vessels from pre-existing vasculature, in order to obtain nutrients required for continued growth and proliferation. Targeting factors that regulate angiogenesis, including the potent promoter vascular endothelial growth factor (VEGF), is therefore an attractive strategy for inhibiting tumor growth. Computational modeling can be used to identify tumor-specific properties that influence the response to anti-angiogenic strategies. Here, we build on our previous systems biology model of VEGF transport and kinetics in tumor-bearing mice to include a tumor compartment whose volume depends on the "angiogenic signal" produced when VEGF binds to its receptors on tumor endothelial cells. We trained and validated the model using published in vivo measurements of xenograft tumor volume, producing a model that accurately predicts the tumor's response to anti-angiogenic treatment. We applied the model to investigate how tumor growth kinetics influence the response to anti-angiogenic treatment targeting VEGF. Based on multivariate regression analysis, we found that certain intrinsic kinetic parameters that characterize the growth of tumors could successfully predict response to anti-VEGF treatment, the reduction in tumor volume. Lastly, we use the trained model to predict the response to anti-VEGF therapy for tumors expressing different levels of VEGF receptors. The model predicts that certain tumors are more sensitive to treatment than others, and the response to treatment shows a nonlinear dependence on the VEGF receptor expression. Overall, this model is a useful tool for predicting how tumors will respond to anti-VEGF treatment, and it complements pre-clinical in vivo mouse studies.

Ossabaw miniature swine were fed an excess calorie, atherogenic diet for 6, 9, or 12 months. Increased body weight, hypertension, and increased plasma cholesterol and triglycerides are described in Table 1. For more detailed interpretations and conclusions about the data, see our associated research study, “Biphasic alterations in coronary smooth muscle Ca2+ regulation during coronary artery disease progression in metabolic syndrome” McKenney-Drake, et al. (2016) [1].

Cholesterol is a multifunctional lipid that plays important metabolic and structural roles in the eukaryotic cell. Despite having diverse lifestyles, the obligate intracellular bacterial pathogens Chlamydia, Coxiella, Anaplasma, Ehrlichia, and Rickettsia all target cholesterol during host cell colonization as a potential source of membrane, as well as a means to manipulate host cell signaling and trafficking. To promote host cell entry, these pathogens utilize cholesterol-rich microdomains known as lipid rafts, which serve as organizational and functional platforms for host signaling pathways involved in phagocytosis. Once a pathogen gains entrance to the intracellular space, it can manipulate host cholesterol trafficking pathways to access nutrient-rich vesicles or acquire membrane components for the bacteria or bacteria-containing vacuole. To acquire cholesterol, these pathogens specifically target host cholesterol metabolism, uptake, efflux, and storage. In this review, we examine the strategies obligate intracellular bacterial pathogens employ to manipulate cholesterol during host cell colonization. Understanding how obligate intracellular pathogens target and use host cholesterol provides critical insight into the host-pathogen relationship.

ABSTRACT Coxiella burnetii is an intracellular bacterial pathogen and a significant cause of culture-negative endocarditis in the United States. Upon infection, the nascent Coxiella phagosome fuses with the host endocytic pathway to form a large lysosome-like vacuole called the parasitophorous vacuole (PV). The PV membrane is rich in sterols, and drugs perturbing host cell cholesterol homeostasis inhibit PV formation and bacterial growth. Using cholesterol supplementation of a cholesterol-free cell model system, we found smaller PVs and reduced Coxiella growth as cellular cholesterol concentration increased. Further, we observed in cells with cholesterol a significant number of nonfusogenic PVs that contained degraded bacteria, a phenotype not observed in cholesterol-free cells. Cholesterol had no effect on axenic Coxiella cultures, indicating that only intracellular bacteria are sensitive to cholesterol. Live-cell microscopy revealed that both plasma membrane-derived cholesterol and the exogenous cholesterol carrier protein low-density lipoprotein (LDL) traffic to the PV. To test the possibility that increasing PV cholesterol levels affects bacterial survival, infected cells were treated with U18666A, a drug that traps cholesterol in lysosomes and PVs. U18666A treatment led to PVs containing degraded bacteria and a significant loss in bacterial viability. The PV pH was significantly more acidic in cells with cholesterol or cells treated with U18666A, and the vacuolar ATPase inhibitor bafilomycin blocked cholesterol-induced PV acidification and bacterial death. Additionally, treatment of infected HeLa cells with several FDA-approved cholesterol-altering drugs led to a loss of bacterial viability, a phenotype also rescued by bafilomycin. Collectively, these data suggest that increasing PV cholesterol further acidifies the PV, leading to Coxiella death. IMPORTANCE The intracellular Gram-negative bacterium Coxiella burnetii is a significant cause of culture-negative infectious endocarditis, which can be fatal if untreated. The existing treatment strategy requires prolonged antibiotic treatment, with a 10-year mortality rate of 19% in treated patients. Therefore, new clinical therapies are needed and can be achieved by better understanding C. burnetii pathogenesis. Upon infection of host cells, C. burnetii grows within a specialized replication niche, the parasitophorous vacuole (PV). Recent data have linked cholesterol to intracellular C. burnetii growth and PV formation, leading us to further decipher the role of cholesterol during C. burnetii-host interaction. We observed that increasing PV cholesterol concentration leads to increased acidification of the PV and bacterial death. Further, treatment with FDA-approved drugs that alter host cholesterol homeostasis also killed C. burnetii through PV acidification. Our findings suggest that targeting host cholesterol metabolism might prove clinically efficacious in controlling C. burnetii infection.